我有一個(gè)輸入文件,其中每個(gè)值都存儲(chǔ)為一個(gè)字符串.

它位于一個(gè)csv文件中,每個(gè)條目都在雙引號(hào)內(nèi).

示例文件：

"column1","column2", "column3", "column4", "column5", "column6"

"AM", "07", "1", "SD", "SD", "CR"

"AM", "08", "1,2,3", "PR,SD,SD", "PR,SD,SD", "PR,SD,SD"

"AM", "01", "2", "SD", "SD", "SD"

只有六列.我需要輸入哪些選項(xiàng)來(lái)pandas read_csv才能正確讀取？

我目前正在嘗試：

import pandas as pd

df = pd.read_csv(file, quotechar='"')

但這給了我錯(cuò)誤信息：

CParserError：標(biāo)記數(shù)據(jù)時(shí)出錯(cuò). C錯(cuò)誤：第3行預(yù)計(jì)6個(gè)字段,見(jiàn)14

這顯然意味著它忽略了”’并將每個(gè)逗號(hào)解析為一個(gè)字段.

但是,對(duì)于第3行,第3列到第6列應(yīng)該是包含逗號(hào)的字符串. (“1,2,3”,“PR,SD,SD”,“PR,SD,SD”,“PR,SD,SD”)

如何讓pandas.read_csv正確解析？

謝謝.

解決方法:

這會(huì)奏效.它回退到python解析器(因?yàn)槟阌蟹浅Ｒ?guī)的分隔符,例如它們是逗號(hào),有時(shí)是空格).如果你只有逗號(hào)它會(huì)使用c-parser并且速度更快.

In [1]: import csv

In [2]: !cat test.csv

"column1","column2", "column3", "column4", "column5", "column6"

"AM", "07", "1", "SD", "SD", "CR"

"AM", "08", "1,2,3", "PR,SD,SD", "PR,SD,SD", "PR,SD,SD"

"AM", "01", "2", "SD", "SD", "SD"

In [3]: pd.read_csv('test.csv',sep=',\s+',quoting=csv.QUOTE_ALL)

pandas/io/parsers.py:637: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.

ParserWarning)

Out[3]:

"column1","column2" "column3" "column4" "column5" "column6"

"AM" "07" "1" "SD" "SD" "CR"

"AM" "08" "1,2,3" "PR,SD,SD" "PR,SD,SD" "PR,SD,SD"

"AM" "01" "2" "SD" "SD" "SD"

標(biāo)簽：python,pandas,csv

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